Picture map of Europe with pins indicating European capital cities

Open Access research with a European policy impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the European Policies Research Centre (EPRC).

EPRC is a leading institute in Europe for comparative research on public policy, with a particular focus on regional development policies. Spanning 30 European countries, EPRC research programmes have a strong emphasis on applied research and knowledge exchange, including the provision of policy advice to EU institutions and national and sub-national government authorities throughout Europe.

Explore research outputs by the European Policies Research Centre...

Classification and de-noising of communication signals using kernel principal component analysis (KPCA)

Koutsogiannis, G. and Soraghan, J.J. (2002) Classification and de-noising of communication signals using kernel principal component analysis (KPCA). In: 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002-05-13 - 2002-05-17, Renaissance Orlando Resort.

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

This paper is concerned with the classification and de-noising problem for non-linear signals. It is known that using kernel functions, a non-linear signal can be transformed into a linear signal in a higher dimensional space. In that feature space, a linear algorithm can be applied to a non-linear problem. It is proposed that using the principal components extracted from the feature space, the signal can be classified correctly in its input space. Additionally, it is shown how this classification process' can be used to de-noise DQPSK communication signals